29 citations · 52 across the 3 of their papers we have counts for
4 papers
Efficient Computation in Adaptive Artificial Spiking Neural Networks
Davide Zambrano, Roeland Nusselder, H. Steven Scholte +1
Artificial Neural Networks (ANNs) are bio-inspired models of neural computation that have proven highly effective. Still, ANNs lack a natural notion of time, and neural units in AN…
Visual pathways from the perspective of cost functions and multi-task deep neural networks
H. Steven Scholte, Max M. Losch, Kandan Ramakrishnan +2
Vision research has been shaped by the seminal insight that we can understand the higher-tier visual cortex from the perspective of multiple functional pathways with different goal…
Efficient forward propagation of time-sequences in convolutional neural networks using Deep Shifting
Koen Groenland, Sander Bohte
When a Convolutional Neural Network is used for on-the-fly evaluation of continuously updating time-sequences, many redundant convolution operations are performed. We propose the m…
Fractionally Predictive Spiking Neurons
Sander M. Bohte, Jaldert O. Rombouts
Recent experimental work has suggested that the neural firing rate can be interpreted as a fractional derivative, at least when signal variation induces neural adaptation. Here, we…